A predictive approach to task scheduling for Big Data in cloud environments using classification algorithms
| Autor: | Apoorvi Sood, Anshuman Chhabra, Vidushi Vashishth |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science Big data Particle swarm optimization 020207 software engineering Cloud computing 02 engineering and technology computer.software_genre Scheduling (computing) Random forest Statistical classification Virtual machine 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing The Internet Data mining business computer |
| Zdroj: | 2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence. |
| DOI: | 10.1109/confluence.2017.7943147 |
| Popis: | There have been many recent developments in integrating the Cloud with the Internet of Τhings (IoT) which comprise of up and coming technologies such as Smart Cities and Smart devices. This federation has resulted in research being directed towards further integration of Big Data with the Cloud, as IoT devices consisting of such technologies generate a continuous stream of sensor data. Thus, in this paper, we seek to present a predictive approach to task scheduling with the aim of reducing the overhead incurred when Big Data is processed on the Cloud. Subsequently, we wish to increase both the efficiency and reliability of the Cloud network while handling Big Data. We present a method of using classification in Machine Learning as a tool for scheduling tasks and assigning them to Virtual Machines (VMs) in the Cloud environment. A comparative study is undertaken to observe which brand of classifiers perform optimally in the given scenario. Particle Swarm Optimization (PSO) is used to generate the dataset which is used to train the classifiers. A number of classification algorithms such as Naive Bayes, Random Forest and Κ Nearest Neighbor are then used to predict the VM best suited to a task in the test dataset. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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